[Serverless Mini Agent] Add Azure App Service Runtime Tags

[duncanpharvey]

What does this PR do?

Adds the following span tags to traces sent by the Serverless Mini Agent in Azure Functions.

• aas.environment.runtime
• aas.environment.runtime_version
• aas.environment.function_runtime

Motivation

https://datadoghq.atlassian.net/browse/SVLS-4935

• Usage tracking for mini agent private beta
• Span tag parity with Datadog Agent

Additional Notes

Updates how Azure Metadata values are retrieved so empty strings are mapped to unknown.

How to test the change?

• Build mini agent locally
• Deploy Azure Function with mini agent binary in root path
• Set DD_MINI_AGENT_PATH
  • Azure: /home/site/wwwroot/datadog-serverless-trace-mini-agent

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 81.25000% with 9 lines in your changes missing coverage. Please review.

Project coverage is 70.40%. Comparing base (8a5d447) to head (7be4fb2).

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #512      +/-   ##
==========================================
+ Coverage   70.38%   70.40%   +0.02%     
==========================================
  Files         204      204              
  Lines       27835    27882      +47     
==========================================
+ Hits        19591    19630      +39     
- Misses       8244     8252       +8     

Components	Coverage Δ
crashtracker	16.70% <ø> (ø)
datadog-alloc	98.76% <ø> (ø)
data-pipeline	51.15% <ø> (ø)
data-pipeline-ffi	0.00% <ø> (ø)
ddcommon	86.49% <100.00%> (+0.36%)	⬆️
ddcommon-ffi	74.15% <ø> (ø)
ddtelemetry	59.37% <ø> (ø)
ipc	84.66% <ø> (ø)
profiling	78.63% <ø> (ø)
profiling-ffi	58.19% <ø> (ø)
serverless	0.00% <ø> (ø)
sidecar	36.19% <ø> (ø)
sidecar-ffi	0.00% <ø> (ø)
spawn-worker	54.98% <ø> (ø)
trace-mini-agent	69.70% <ø> (ø)
trace-normalization	97.79% <ø> (ø)
trace-obfuscation	95.75% <ø> (ø)
trace-protobuf	77.16% <ø> (ø)
trace-utils	90.84% <0.00%> (-0.37%)	⬇️

[alexgallotta]

Looks good! I would add a test with the failing case to make sure it works

[pr-commenter]

Benchmarks

Comparison

Parameters

	Baseline	Candidate
config	baseline	candidate
git_branch	main	duncan-harvey/serverless-runtime-tags
git_commit_date	1719860752	1719928086
git_commit_sha	8a5d447	7be4fb2

See matching parameters

	Baseline	Candidate
ci_job_date	1719928335	1719928335
ci_job_id	559707445	559707445
ci_pipeline_id	38132004	38132004
cpu_model	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz
iterations	717.0	717.0

Summary

Found 0 performance improvements and 0 performance regressions! Performance is the same for 1 metrics, 0 unstable metrics.

Candidate

Candidate benchmark details

Group 1

iterations	config	cpu_model	ci_job_date	ci_job_id	ci_pipeline_id	git_commit_sha	git_commit_date	git_branch
717.0	candidate	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	1719928335	559707445	38132004	7be4fb2	1719928086	duncan-harvey/serverless-runtime-tags

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
sql/obfuscate_sql_string	execution_time	69.753µs	69.816µs ± 0.034µs	69.811µs ± 0.021µs	69.837µs	69.878µs	69.897µs	69.904µs	0.13%	0.407	-0.389	0.05%	0.003µs	1	100

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[69.810µs; 69.823µs] or [-0.010%; +0.010%]	None	None	None

Warnings

Scenario: sql/obfuscate_sql_string, Metric: execution_time

Measurements are autocorrelated.

Autocorrelation is present for lags 1..10.

The measurements are not independent, thus confidence intervals
may be less precise.
---------------------------------------------------------------------------

Scenario: sql/obfuscate_sql_string, Metric: execution_time

Sample size is 100, which is lower than 105.

The minimal sample size in case of normal distribution to achieve significance
level of 0.05 for difference of means with effect size Cohen's d = 0.5 must be at
least 105.

The conclusions from confidence intervals may be invalid.
---------------------------------------------------------------------------

Baseline

Baseline benchmark details

Group 1

iterations	config	cpu_model	ci_job_date	ci_job_id	ci_pipeline_id	git_commit_sha	git_commit_date	git_branch
717.0	baseline	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	1719928335	559707445	38132004	8a5d447	1719860752	main

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
sql/obfuscate_sql_string	execution_time	69.787µs	69.917µs ± 0.046µs	69.920µs ± 0.033µs	69.951µs	69.985µs	70.004µs	70.006µs	0.12%	-0.330	-0.305	0.07%	0.005µs	1	100

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[69.908µs; 69.926µs] or [-0.013%; +0.013%]	None	None	None

Warnings

Scenario: sql/obfuscate_sql_string, Metric: execution_time

Measurements are autocorrelated.

Autocorrelation is present for lags 1..10.

The measurements are not independent, thus confidence intervals
may be less precise.
---------------------------------------------------------------------------

Scenario: sql/obfuscate_sql_string, Metric: execution_time

Sample size is 100, which is lower than 105.

The minimal sample size in case of normal distribution to achieve significance
level of 0.05 for difference of means with effect size Cohen's d = 0.5 must be at
least 105.

The conclusions from confidence intervals may be invalid.
---------------------------------------------------------------------------